Applying Machine Learning to Facilitate Autism Diagnostics: Pitfalls and Promises / Daniel BONE in Journal of Autism and Developmental Disorders, 45-5 (May 2015)  

Public ISBD [article]  inJournal of Autism and Developmental Disorders > 45-5 (May 2015) . - p.1121-1136 Titre : Applying Machine Learning to Facilitate Autism Diagnostics: Pitfalls and Promises Type de document : texte imprimé Auteurs : Daniel BONE, Auteur ; Matthew GOODWIN, Auteur ; Matthew P. BLACK, Auteur ; Chi-Chun LEE, Auteur ; Kartik AUDHKHASI, Auteur ; Shrikanth NARAYANAN, Auteur Article en page(s) : p.1121-1136 Langues : Anglais (eng) Mots-clés : Autism diagnostic observation schedule  Autism diagnostic interview  Machine learning  Signal processing  Autism  Diagnosis Index. décimale : PER Périodiques Résumé : Machine learning has immense potential to enhance diagnostic and intervention research in the behavioral sciences, and may be especially useful in investigations involving the highly prevalent and heterogeneous syndrome of autism spectrum disorder. However, use of machine learning in the absence of clinical domain expertise can be tenuous and lead to misinformed conclusions. To illustrate this concern, the current paper critically evaluates and attempts to reproduce results from two studies (Wall et al. in Transl Psychiatry 2(4):e100, 2012a; PloS One 7(8), 2012b) that claim to drastically reduce time to diagnose autism using machine learning. Our failure to generate comparable findings to those reported by Wall and colleagues using larger and more balanced data underscores several conceptual and methodological problems associated with these studies. We conclude with proposed best-practices when using machine learning in autism research, and highlight some especially promising areas for collaborative work at the intersection of computational and behavioral science. En ligne : http://dx.doi.org/10.1007/s10803-014-2268-6 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=259 [article] Applying Machine Learning to Facilitate Autism Diagnostics: Pitfalls and Promises [texte imprimé] / Daniel BONE, Auteur ; Matthew GOODWIN, Auteur ; Matthew P. BLACK, Auteur ; Chi-Chun LEE, Auteur ; Kartik AUDHKHASI, Auteur ; Shrikanth NARAYANAN, Auteur . - p.1121-1136. Langues : Anglais (eng) in Journal of Autism and Developmental Disorders > 45-5 (May 2015) . - p.1121-1136 Mots-clés : Autism diagnostic observation schedule  Autism diagnostic interview  Machine learning  Signal processing  Autism  Diagnosis Index. décimale : PER Périodiques Résumé : Machine learning has immense potential to enhance diagnostic and intervention research in the behavioral sciences, and may be especially useful in investigations involving the highly prevalent and heterogeneous syndrome of autism spectrum disorder. However, use of machine learning in the absence of clinical domain expertise can be tenuous and lead to misinformed conclusions. To illustrate this concern, the current paper critically evaluates and attempts to reproduce results from two studies (Wall et al. in Transl Psychiatry 2(4):e100, 2012a; PloS One 7(8), 2012b) that claim to drastically reduce time to diagnose autism using machine learning. Our failure to generate comparable findings to those reported by Wall and colleagues using larger and more balanced data underscores several conceptual and methodological problems associated with these studies. We conclude with proposed best-practices when using machine learning in autism research, and highlight some especially promising areas for collaborative work at the intersection of computational and behavioral science. En ligne : http://dx.doi.org/10.1007/s10803-014-2268-6 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=259

Atypical Emotional Electrodermal Activity in Toddlers with Autism Spectrum Disorder / Angelina VERNETTI in Autism Research, 13-9 (September 2020)  

Public ISBD [article]  inAutism Research > 13-9 (September 2020) . - p.1476-1488 Titre : Atypical Emotional Electrodermal Activity in Toddlers with Autism Spectrum Disorder Type de document : texte imprimé Auteurs : Angelina VERNETTI, Auteur ; Frederick SHIC, Auteur ; Laura BOCCANFUSO, Auteur ; Suzanne MACARI, Auteur ; Finola KANE-GRADE, Auteur ; Anna MILGRAMM, Auteur ; Emily HILTON, Auteur ; Perrine HEYMANN, Auteur ; Matthew GOODWIN, Auteur ; Katarzyna CHAWARSKA, Auteur Article en page(s) : p.1476-1488 Langues : Anglais (eng) Index. décimale : PER Périodiques Résumé : Past studies in autism spectrum disorder (ASD) indicate atypical peripheral physiological arousal. However, the conditions under which these atypicalities arise and their link with behavioral emotional expressions and core ASD symptoms remain uncertain. Given the importance of physiological arousal in affective, learning, and cognitive processes, the current study examined changes in skin conductance level (ΔSCL) in 41 toddlers with ASD (mean age: 22.7 months, SD: 2.9) and 32 age-matched toddlers with typical development (TD) (mean age: 21.6 months, SD: 3.6) in response to probes designed to induce anger, joy, and fear emotions. The magnitude of ΔSCL was comparable during anger (P = 0.206, d = 0.30) and joy (P = 0.996, d = 0.01) conditions, but significantly lower during the fear condition (P = 0.001, d = 0.83) in toddlers with ASD compared to TD peers. In the combined samples, ΔSCL positively correlated with intensity of behavioral emotional expressivity during the anger (r[71] = 0.36, P = 0.002) and fear (r[68] = 0.32, P = 0.007) conditions, but not in the joy (r[69] = −0.15, P = 0.226) condition. Finally, ΔSCL did not associate with autism symptom severity in any emotion-eliciting condition in the ASD group. Toddlers with ASD displayed attenuated ΔSCL to situations aimed at eliciting fear, which may forecast the emergence of highly prevalent internalizing and externalizing problems in this population. The study putatively identifies ΔSCL as a dimension not associated with severity of autism but with behavioral responses in negatively emotionally challenging events and provides support for the feasibility, validity, and incipient utility of examining ΔSCL in response to emotional challenges in very young children. Lay Summary Physiological arousal was measured in toddlers with autism exposed to frustrating, pleasant, and threatening tasks. Compared to typically developing peers, toddlers with autism showed comparable arousal responses to frustrating and pleasant events, but lower responses to threatening events. Importantly, physiological arousal and behavioral expressions were aligned during frustrating and threatening events, inviting exploration of physiological arousal to measure responses to emotional challenges. Furthermore, this study advances the understanding of precursors to emotional and behavioral problems common in older children with autism. Autism Res 2020, 13: 1476–1488. © 2020 International Society for Autism Research, Wiley Periodicals, Inc. En ligne : http://dx.doi.org/10.1002/aur.2374 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=431 [article] Atypical Emotional Electrodermal Activity in Toddlers with Autism Spectrum Disorder [texte imprimé] / Angelina VERNETTI, Auteur ; Frederick SHIC, Auteur ; Laura BOCCANFUSO, Auteur ; Suzanne MACARI, Auteur ; Finola KANE-GRADE, Auteur ; Anna MILGRAMM, Auteur ; Emily HILTON, Auteur ; Perrine HEYMANN, Auteur ; Matthew GOODWIN, Auteur ; Katarzyna CHAWARSKA, Auteur . - p.1476-1488. Langues : Anglais (eng) in Autism Research > 13-9 (September 2020) . - p.1476-1488 Index. décimale : PER Périodiques Résumé : Past studies in autism spectrum disorder (ASD) indicate atypical peripheral physiological arousal. However, the conditions under which these atypicalities arise and their link with behavioral emotional expressions and core ASD symptoms remain uncertain. Given the importance of physiological arousal in affective, learning, and cognitive processes, the current study examined changes in skin conductance level (ΔSCL) in 41 toddlers with ASD (mean age: 22.7 months, SD: 2.9) and 32 age-matched toddlers with typical development (TD) (mean age: 21.6 months, SD: 3.6) in response to probes designed to induce anger, joy, and fear emotions. The magnitude of ΔSCL was comparable during anger (P = 0.206, d = 0.30) and joy (P = 0.996, d = 0.01) conditions, but significantly lower during the fear condition (P = 0.001, d = 0.83) in toddlers with ASD compared to TD peers. In the combined samples, ΔSCL positively correlated with intensity of behavioral emotional expressivity during the anger (r[71] = 0.36, P = 0.002) and fear (r[68] = 0.32, P = 0.007) conditions, but not in the joy (r[69] = −0.15, P = 0.226) condition. Finally, ΔSCL did not associate with autism symptom severity in any emotion-eliciting condition in the ASD group. Toddlers with ASD displayed attenuated ΔSCL to situations aimed at eliciting fear, which may forecast the emergence of highly prevalent internalizing and externalizing problems in this population. The study putatively identifies ΔSCL as a dimension not associated with severity of autism but with behavioral responses in negatively emotionally challenging events and provides support for the feasibility, validity, and incipient utility of examining ΔSCL in response to emotional challenges in very young children. Lay Summary Physiological arousal was measured in toddlers with autism exposed to frustrating, pleasant, and threatening tasks. Compared to typically developing peers, toddlers with autism showed comparable arousal responses to frustrating and pleasant events, but lower responses to threatening events. Importantly, physiological arousal and behavioral expressions were aligned during frustrating and threatening events, inviting exploration of physiological arousal to measure responses to emotional challenges. Furthermore, this study advances the understanding of precursors to emotional and behavioral problems common in older children with autism. Autism Res 2020, 13: 1476–1488. © 2020 International Society for Autism Research, Wiley Periodicals, Inc. En ligne : http://dx.doi.org/10.1002/aur.2374 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=431

Automated Detection of Stereotypical Motor Movements / Matthew GOODWIN in Journal of Autism and Developmental Disorders, 41-6 (June 2011)  

Public ISBD [article]  inJournal of Autism and Developmental Disorders > 41-6 (June 2011) . - p.770-782 Titre : Automated Detection of Stereotypical Motor Movements Type de document : texte imprimé Auteurs : Matthew GOODWIN, Auteur ; Stephen S. INTILLE, Auteur ; Fahd ALBINALI, Auteur ; Wayne F. VELICER, Auteur Année de publication : 2011 Article en page(s) : p.770-782 Langues : Anglais (eng) Mots-clés : Stereotypical motor movement  Accelerometry  Pattern recognition Index. décimale : PER Périodiques Résumé : To overcome problems with traditional methods for measuring stereotypical motor movements in persons with Autism Spectrum Disorders (ASD), we evaluated the use of wireless three-axis accelerometers and pattern recognition algorithms to automatically detect body rocking and hand flapping in children with ASD. Findings revealed that, on average, pattern recognition algorithms correctly identified approximately 90% of stereotypical motor movements repeatedly observed in both laboratory and classroom settings. Precise and efficient recording of stereotypical motor movements could enable researchers and clinicians to systematically study what functional relations exist between these behaviors and specific antecedents and consequences. These measures could also facilitate efficacy studies of behavioral and pharmacologic interventions intended to replace or decrease the incidence or severity of stereotypical motor movements. En ligne : http://dx.doi.org/10.1007/s10803-010-1102-z Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=127 [article] Automated Detection of Stereotypical Motor Movements [texte imprimé] / Matthew GOODWIN, Auteur ; Stephen S. INTILLE, Auteur ; Fahd ALBINALI, Auteur ; Wayne F. VELICER, Auteur . - 2011 . - p.770-782. Langues : Anglais (eng) in Journal of Autism and Developmental Disorders > 41-6 (June 2011) . - p.770-782 Mots-clés : Stereotypical motor movement  Accelerometry  Pattern recognition Index. décimale : PER Périodiques Résumé : To overcome problems with traditional methods for measuring stereotypical motor movements in persons with Autism Spectrum Disorders (ASD), we evaluated the use of wireless three-axis accelerometers and pattern recognition algorithms to automatically detect body rocking and hand flapping in children with ASD. Findings revealed that, on average, pattern recognition algorithms correctly identified approximately 90% of stereotypical motor movements repeatedly observed in both laboratory and classroom settings. Precise and efficient recording of stereotypical motor movements could enable researchers and clinicians to systematically study what functional relations exist between these behaviors and specific antecedents and consequences. These measures could also facilitate efficacy studies of behavioral and pharmacologic interventions intended to replace or decrease the incidence or severity of stereotypical motor movements. En ligne : http://dx.doi.org/10.1007/s10803-010-1102-z Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=127

Automated recognition of spontaneous facial expression in individuals with autism spectrum disorder: parsing response variability / Abigail BANGERTER in Molecular Autism, 11 (2020)  

Public ISBD [article]  inMolecular Autism > 11 (2020) . - 31 p. Titre : Automated recognition of spontaneous facial expression in individuals with autism spectrum disorder: parsing response variability Type de document : texte imprimé Auteurs : Abigail BANGERTER, Auteur ; Meenakshi CHATTERJEE, Auteur ; Joseph MANFREDONIA, Auteur ; Nikolay V. MANYAKOV, Auteur ; Seth NESS, Auteur ; Matthew A. BOICE, Auteur ; Andrew SKALKIN, Auteur ; Matthew GOODWIN, Auteur ; Geraldine DAWSON, Auteur ; Robert L. HENDREN, Auteur ; Bennett L. LEVENTHAL, Auteur ; Frederick SHIC, Auteur ; Gahan PANDINA, Auteur Article en page(s) : 31 p. Langues : Anglais (eng) Mots-clés : Autism spectrum disorder  Emotional regulation  Emotions  Facial expression  Impulsive behavior  LLC, and may hold company equity. AS was an employee of Janssen Research &  Development at the time of the study. MSG has received research and consulting  funding from Janssen Research & Development. GD is on the Scientific Advisory Boards  of Janssen Research & Development  Akili, Inc.  LabCorp, Inc.  and Roche  Pharmaceutical Company  is a consultant for Apple, Inc  Gerson Lehrman Group  Guidepoint, Inc.  and Axial Ventures  has received grant funding from Janssen  Research & Development  and is the CEO of DASIO, LLC. GD receives royalties from  Guilford Press, Springer, and Oxford University Press. RH received reimbursement for  consultation from Janssen Research & Development. BL has received research grant  funding from the NIH  is a consultant to Janssen Research & Development, the  Illinois Children’s Healthcare Foundation  and is a board member of the Brain  Research Foundation. FS is on the Scientific Advisory Board, is a consultant to and  received grant funding from Janssen Research & Development, and has also received  grant funding from Roche. Index. décimale : PER Périodiques Résumé : BACKGROUND: Reduction or differences in facial expression are a core diagnostic feature of autism spectrum disorder (ASD), yet evidence regarding the extent of this discrepancy is limited and inconsistent. Use of automated facial expression detection technology enables accurate and efficient tracking of facial expressions that has potential to identify individual response differences. METHODS: Children and adults with ASD (N = 124) and typically developing (TD, N = 41) were shown short clips of "funny videos." Using automated facial analysis software, we investigated differences between ASD and TD groups and within the ASD group in evidence of facial action unit (AU) activation related to the expression of positive facial expression, in particular, a smile. RESULTS: Individuals with ASD on average showed less evidence of facial AUs (AU12, AU6) relating to positive facial expression, compared to the TD group (p < .05, r = - 0.17). Using Gaussian mixture model for clustering, we identified two distinct distributions within the ASD group, which were then compared to the TD group. One subgroup (n = 35), termed "over-responsive," expressed more intense positive facial expressions in response to the videos than the TD group (p < .001, r = 0.31). The second subgroup (n = 89), ("under-responsive"), displayed fewer, less intense positive facial expressions in response to videos than the TD group (p < .001; r = - 0.36). The over-responsive subgroup differed from the under-responsive subgroup in age and caregiver-reported impulsivity (p < .05, r = 0.21). Reduced expression in the under-responsive, but not the over-responsive group, was related to caregiver-reported social withdrawal (p < .01, r = - 0.3). LIMITATIONS: This exploratory study does not account for multiple comparisons, and future work will have to ascertain the strength and reproducibility of all results. Reduced displays of positive facial expressions do not mean individuals with ASD do not experience positive emotions. CONCLUSIONS: Individuals with ASD differed from the TD group in their facial expressions of positive emotion in response to "funny videos." Identification of subgroups based on response may help in parsing heterogeneity in ASD and enable targeting of treatment based on subtypes. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02299700. Registration date: November 24, 2014. En ligne : http://dx.doi.org/10.1186/s13229-020-00327-4 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=427 [article] Automated recognition of spontaneous facial expression in individuals with autism spectrum disorder: parsing response variability [texte imprimé] / Abigail BANGERTER, Auteur ; Meenakshi CHATTERJEE, Auteur ; Joseph MANFREDONIA, Auteur ; Nikolay V. MANYAKOV, Auteur ; Seth NESS, Auteur ; Matthew A. BOICE, Auteur ; Andrew SKALKIN, Auteur ; Matthew GOODWIN, Auteur ; Geraldine DAWSON, Auteur ; Robert L. HENDREN, Auteur ; Bennett L. LEVENTHAL, Auteur ; Frederick SHIC, Auteur ; Gahan PANDINA, Auteur . - 31 p. Langues : Anglais (eng) in Molecular Autism > 11 (2020) . - 31 p. Mots-clés : Autism spectrum disorder  Emotional regulation  Emotions  Facial expression  Impulsive behavior  LLC, and may hold company equity. AS was an employee of Janssen Research &  Development at the time of the study. MSG has received research and consulting  funding from Janssen Research & Development. GD is on the Scientific Advisory Boards  of Janssen Research & Development  Akili, Inc.  LabCorp, Inc.  and Roche  Pharmaceutical Company  is a consultant for Apple, Inc  Gerson Lehrman Group  Guidepoint, Inc.  and Axial Ventures  has received grant funding from Janssen  Research & Development  and is the CEO of DASIO, LLC. GD receives royalties from  Guilford Press, Springer, and Oxford University Press. RH received reimbursement for  consultation from Janssen Research & Development. BL has received research grant  funding from the NIH  is a consultant to Janssen Research & Development, the  Illinois Children’s Healthcare Foundation  and is a board member of the Brain  Research Foundation. FS is on the Scientific Advisory Board, is a consultant to and  received grant funding from Janssen Research & Development, and has also received  grant funding from Roche. Index. décimale : PER Périodiques Résumé : BACKGROUND: Reduction or differences in facial expression are a core diagnostic feature of autism spectrum disorder (ASD), yet evidence regarding the extent of this discrepancy is limited and inconsistent. Use of automated facial expression detection technology enables accurate and efficient tracking of facial expressions that has potential to identify individual response differences. METHODS: Children and adults with ASD (N = 124) and typically developing (TD, N = 41) were shown short clips of "funny videos." Using automated facial analysis software, we investigated differences between ASD and TD groups and within the ASD group in evidence of facial action unit (AU) activation related to the expression of positive facial expression, in particular, a smile. RESULTS: Individuals with ASD on average showed less evidence of facial AUs (AU12, AU6) relating to positive facial expression, compared to the TD group (p < .05, r = - 0.17). Using Gaussian mixture model for clustering, we identified two distinct distributions within the ASD group, which were then compared to the TD group. One subgroup (n = 35), termed "over-responsive," expressed more intense positive facial expressions in response to the videos than the TD group (p < .001, r = 0.31). The second subgroup (n = 89), ("under-responsive"), displayed fewer, less intense positive facial expressions in response to videos than the TD group (p < .001; r = - 0.36). The over-responsive subgroup differed from the under-responsive subgroup in age and caregiver-reported impulsivity (p < .05, r = 0.21). Reduced expression in the under-responsive, but not the over-responsive group, was related to caregiver-reported social withdrawal (p < .01, r = - 0.3). LIMITATIONS: This exploratory study does not account for multiple comparisons, and future work will have to ascertain the strength and reproducibility of all results. Reduced displays of positive facial expressions do not mean individuals with ASD do not experience positive emotions. CONCLUSIONS: Individuals with ASD differed from the TD group in their facial expressions of positive emotion in response to "funny videos." Identification of subgroups based on response may help in parsing heterogeneity in ASD and enable targeting of treatment based on subtypes. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02299700. Registration date: November 24, 2014. En ligne : http://dx.doi.org/10.1186/s13229-020-00327-4 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=427

Automatic Recognition of Posed Facial Expression of Emotion in Individuals with Autism Spectrum Disorder / J. MANFREDONIA in Journal of Autism and Developmental Disorders, 49-1 (January 2019)  

Public ISBD [article]  inJournal of Autism and Developmental Disorders > 49-1 (January 2019) . - p.279-293 Titre : Automatic Recognition of Posed Facial Expression of Emotion in Individuals with Autism Spectrum Disorder Type de document : texte imprimé Auteurs : J. MANFREDONIA, Auteur ; Abigail BANGERTER, Auteur ; N. V. MANYAKOV, Auteur ; S. NESS, Auteur ; D. LEWIN, Auteur ; A. SKALKIN, Auteur ; Matthew A. BOICE, Auteur ; Matthew GOODWIN, Auteur ; G. DAWSON, Auteur ; Robert L. HENDREN, Auteur ; B. LEVENTHAL, Auteur ; F. SHIC, Auteur ; Gahan PANDINA, Auteur Article en page(s) : p.279-293 Langues : Anglais (eng) Mots-clés : Asd  Automated  Emotion  Expression  Facet  Facial Index. décimale : PER Périodiques Résumé : Facial expression is impaired in autism spectrum disorder (ASD), but rarely systematically studied. We focus on the ability of individuals with ASD to produce facial expressions of emotions in response to a verbal prompt. We used the Janssen Autism Knowledge Engine (JAKE((R))), including automated facial expression analysis software (FACET) to measure facial expressions in individuals with ASD (n = 144) and a typically developing (TD) comparison group (n = 41). Differences in ability to produce facial expressions were observed between ASD and TD groups, demonstrated by activation of facial action units (happy, scared, surprised, disgusted, but not angry or sad). Activation of facial action units correlated with parent-reported social communication skills. This approach has potential for diagnostic and response to intervention measures.Trial Registration NCT02299700. En ligne : http://dx.doi.org/10.1007/s10803-018-3757-9 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=377 [article] Automatic Recognition of Posed Facial Expression of Emotion in Individuals with Autism Spectrum Disorder [texte imprimé] / J. MANFREDONIA, Auteur ; Abigail BANGERTER, Auteur ; N. V. MANYAKOV, Auteur ; S. NESS, Auteur ; D. LEWIN, Auteur ; A. SKALKIN, Auteur ; Matthew A. BOICE, Auteur ; Matthew GOODWIN, Auteur ; G. DAWSON, Auteur ; Robert L. HENDREN, Auteur ; B. LEVENTHAL, Auteur ; F. SHIC, Auteur ; Gahan PANDINA, Auteur . - p.279-293. Langues : Anglais (eng) in Journal of Autism and Developmental Disorders > 49-1 (January 2019) . - p.279-293 Mots-clés : Asd  Automated  Emotion  Expression  Facet  Facial Index. décimale : PER Périodiques Résumé : Facial expression is impaired in autism spectrum disorder (ASD), but rarely systematically studied. We focus on the ability of individuals with ASD to produce facial expressions of emotions in response to a verbal prompt. We used the Janssen Autism Knowledge Engine (JAKE((R))), including automated facial expression analysis software (FACET) to measure facial expressions in individuals with ASD (n = 144) and a typically developing (TD) comparison group (n = 41). Differences in ability to produce facial expressions were observed between ASD and TD groups, demonstrated by activation of facial action units (happy, scared, surprised, disgusted, but not angry or sad). Activation of facial action units correlated with parent-reported social communication skills. This approach has potential for diagnostic and response to intervention measures.Trial Registration NCT02299700. En ligne : http://dx.doi.org/10.1007/s10803-018-3757-9 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=377

Catalysts for Change: The Role of Small Business Funders in the Creation and Dissemination of Innovation / Frederick SHIC in Journal of Autism and Developmental Disorders, 45-12 (December 2015)  

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Clinical Validation of the Autism Behavior Inventory: Caregiver-Rated Assessment of Core and Associated Symptoms of Autism Spectrum Disorder / Abigail BANGERTER in Journal of Autism and Developmental Disorders, 50-6 (June 2020)  

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A comparison of autonomic, behavioral, and parent-report measures of sensory sensitivity in young children with autism / Cooper R. WOODARD in Research in Autism Spectrum Disorders, 6-3 (July-September 2012)  

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Enhancing and Accelerating the Pace of Autism Research and Treatment: The Promise of Developing Innovative Technology / Matthew GOODWIN in Focus on Autism and Other Developmental Disabilities, 23-2 (June 2008)  

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Evaluating commercially available wireless cardiovascular monitors for measuring and transmitting real-time physiological responses in children with autism / H. J. NUSKE in Autism Research, 15-1 (January 2022)  

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A framework of evidence-based practice for digital support, co-developed with and for the autism community / Vanessa ZERVOGIANNI in Autism, 24-6 (August 2020)  

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Introduction to Technologies in the Daily Lives of Individuals with Autism / Frederick SHIC in Journal of Autism and Developmental Disorders, 45-12 (December 2015)  

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Mapping the time course of overt emotion dysregulation, self-injurious behavior, and aggression in psychiatrically hospitalized autistic youth: A naturalistic study / Jessie B. NORTHRUP in Autism Research, 15-10 (October 2022)  

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Observed emotional reactivity in response to frustration tasks in psychiatrically hospitalized youth with autism spectrum disorder / Jessie B. NORTHRUP in Autism, 24-4 (May 2020)  

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A placebo double-blind pilot study of dextromethorphan for problematic behaviors in children with autism / Cooper R. WOODARD in Autism, 11-1 (January 2007)  

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